NiamonX Graph

NiamonX Graph Docs

What is NiamonX Graph?

NiamonX Graph is a new instrument in the NiamonX product line designed for large-scale data visualization, relationship analysis, and collaborative intelligence workflows.

It enables analysts, investigators, and security teams to transform massive structured and semi-structured datasets into interactive, dynamic graph environments – without complex setup or additional installations.

NiamonX Graph is fully integrated into the NiamonX ecosystem and can be accessed directly from your dashboard by creating a new Graph Workspace.


Core Capabilities

Large-Scale Data Visualization

NiamonX Graph is engineered to handle high-volume datasets and complex entity relationships. Whether working with breach intelligence, infostealer logs, domain intelligence, blockchain entities, or sanctions data – the system renders large graphs in a structured and performance-optimized environment.

Smart Relationship Engine

Thanks to an intelligent relationship mapping system, entities are automatically correlated and linked using contextual logic, cross-dataset references, and enrichment signals.
This ensures that large data volumes are not just displayed – they are meaningfully connected.

The platform helps analysts:


50+ Enrichment Transformers

NiamonX Graph includes 50+ integrated transformers that enrich and expand graph nodes with additional intelligence.

These transformers can:

Each transformer adds structured intelligence to the graph, enabling deeper analytical insights and faster investigation workflows.


Collaborative Intelligence

NiamonX Graph supports collaborative workspaces, allowing teams to:

For controlled sharing, graphs can also be exported or shared publicly via secure links — making it easier to present findings to stakeholders, partners, or clients.


Built for Modern Threat Intelligence

As part of the NiamonX ecosystem, NiamonX Graph integrates seamlessly with:

This allows users to move from search results to structured graph analysis in seconds.


Why NiamonX Graph?

NiamonX Graph is not just a visualization tool – it is a high-performance intelligence environment designed to connect large datasets in the most meaningful way possible.

By combining:

NiamonX Graph empowers investigators to see connections that would otherwise remain hidden in massive volumes of data.

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Navigate the Graph (Web App) Interface

The NiamonX Graph interface is structured into three primary sections:

  1. Top Navigation Bar

  2. Entity Palette (Left Sidebar)

  3. Graph Workspace & Intelligence Panel (Center + Right Panel)

Each section is designed to support large-scale graph investigations, enrichment workflows, and collaborative intelligence operations.

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1. Top Navigation Bar

The top bar provides global controls for graph management, enrichment execution, collaboration, and navigation.

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Identity & Workspace Area

• NiamonX Graph

Displays the active environment and current workspace.

• Profile

Shows the active user account and allows access to profile settings.

• Plan

Displays your current subscription tier and available capabilities.


Graph Management Controls

• Select Graph

Switch between saved graph workspaces.

• Create New Graph

Create a new blank investigation workspace.

• Edit Name

Rename the active graph workspace.

• Layouts

Apply automatic graph layout algorithms (e.g., force layout, hierarchical, radial) to optimize visualization.

• FIT

Automatically centers and scales the graph to fit the screen.

• Undo / Redo

Revert or reapply actions such as node creation, deletion, or transformer execution.


Intelligence Execution Controls

• Quick Run (Text Input + Run)

Enter a value (domain, email, IP, hash, etc.) and instantly create a node in the graph.

• Info

Displays contextual information about the current graph or selected node.

• Share Graph

Generate a secure public or restricted link to share your graph.

Supports:


Search & Data Management

• Search Nodes

Search for nodes within the active graph.

• Export

Export graph data in supported formats (e.g., JSON, structured intelligence format).

• Import

Import previously exported graphs or structured intelligence datasets.

2. Entity Palette (Left Sidebar)

The left sidebar is your entity creation and investigation entry point.

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Entity Palette

Contains all available entity types grouped by categories.

Search Entities

Quickly filter entity types.


Categories

Entities are grouped logically, for example:


Entities

Each entity represents a structured data object.

Examples:

To add an entity:

  1. Drag it into the graph area

  2. Or use Quick Run

3. Graph View (Center Workspace)

The central workspace is where investigation takes place.

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Nodes

Each node represents an entity:


Connections (Edges)

Edges represent relationships between entities:


Smart Relationship Engine

NiamonX Graph intelligently links entities across datasets using:

Large datasets are automatically structured to avoid clutter and maximize analytical clarity.


4. Intelligence & Node Panel (Right Sidebar)

When a node is selected, the right panel displays detailed intelligence.

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Node Details

Displays:


Edit / Delete Node

Modify or remove nodes from the graph.


Notes

Add investigation notes to a node:

Useful for collaborative investigations.


Properties

Displays structured JSON-like metadata for the node, including:


Search Transformer

Search among 50+ available enrichment transformers.


Transformers

Transformers expand nodes with additional intelligence.

Examples:


Cost per Request

Each transformer displays resource cost per execution, allowing users to manage API credits efficiently.


Complete Workflow Example

  1. Create a new graph.

  2. Add a Domain node using Quick Run.

  3. Run DNS transformers.

  4. Expand infrastructure nodes.

  5. Run breach enrichment.

  6. Analyze relationships.

  7. Add notes.

  8. Share the graph with stakeholders.

  9. Export structured intelligence if needed.


Designed for Large-Scale Intelligence

The interface is optimized for:

NiamonX Graph ensures that even massive interconnected datasets remain structured, readable, and actionable.

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